{"title":"集成作为分段线性分类器","authors":"P. Hartono, S. Hashimoto","doi":"10.1109/HIS.2006.24","DOIUrl":null,"url":null,"abstract":"In this paper we analyze the performance of a neural network ensemble in performing piecewise linear classification by automatically decomposing a non-linear problem into several linear sub-problems. The strength and weakness of this neural network ensemble with respect to MLP and Perceptron, and the diversity in the ensemble¿s modules, created as the result of the competitive learning process, are the main focus of this paper.","PeriodicalId":150732,"journal":{"name":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Ensemble as a Piecewise Linear Classifier\",\"authors\":\"P. Hartono, S. Hashimoto\",\"doi\":\"10.1109/HIS.2006.24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we analyze the performance of a neural network ensemble in performing piecewise linear classification by automatically decomposing a non-linear problem into several linear sub-problems. The strength and weakness of this neural network ensemble with respect to MLP and Perceptron, and the diversity in the ensemble¿s modules, created as the result of the competitive learning process, are the main focus of this paper.\",\"PeriodicalId\":150732,\"journal\":{\"name\":\"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HIS.2006.24\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HIS.2006.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we analyze the performance of a neural network ensemble in performing piecewise linear classification by automatically decomposing a non-linear problem into several linear sub-problems. The strength and weakness of this neural network ensemble with respect to MLP and Perceptron, and the diversity in the ensemble¿s modules, created as the result of the competitive learning process, are the main focus of this paper.
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